MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products

Table 4 Results of the PTML regression model

Model	Input Vars^a	Symbol	Coeff.^b	Δee_R(%)_qr^b	S.E.^c	t^d	p-level^e
PMTL	ΔLoad(%)_qr	ΔV₃(c_qi, c_rj)	a₁	− 0.82	0.03243	− 25.3154	< 0.005
	ΔT(oC)_qr	ΔV₁(c_qi, c_rj)	a₂	− 0.34	0.00594	− 57.8960	< 0.005
	Δt(h)_qr	ΔV₂(c_qi, c_rj)	a₃	0.21	0.00476	44.4627	< 0.005
	α(Cat_q, Cat_r)_Cuns	ΔD₄(m_3qi, m_3rj)₂	b₁	− 174.37	2.67954	− 65.0741	< 0.005
	α(Prod_q, Prod_r)_HetNoX	ΔD₄(m_5qi, m_5rj)₄	b₂	− 1534.17	26.38185	− 58.1525	< 0.005
	EA(Prod_q, Prod_r)_Csat	ΔD₅(m_5qi, m_5rj)₁	b₃	− 215.98	3.38484	− 63.8086	< 0.005
	EA(Cat_q, Cat_r)_HetNoX	ΔD₅(m_3qi, m_3rj)₄	b₄	− 1747.12	26.48292	− 65.9715	< 0.005
	χ(Nuc_q, Nuc_r)_Het	ΔD₃(m_2qi, m_2rj)₃	b₅	− 42.49	1.33694	− 31.7788	< 0.005
	χ(Cat_q, Cat_r))_HetNoX	ΔD₃(m_3qi, m_3rj)₄	b₆	750.76	8.98832	83.5259	< 0.005
	V(Sub_q, Sub_r)_Tot	ΔD₂(m_1qi, m_1rj)₅	b₇	− 34.19	0.70023	− 48.8225	< 0.005
	Zv(Cat_q, Cat_r)_Cuns	ΔD₁(m_3qi, m_3rj)₂	b₈	22.04	1.16398	18.9356	< 0.005
	Zv(Solv_q, Solv_r)_Cuns	ΔD₁(m_4qi, m_4rj)₂	b₉	− 12.46	0.16653	− 74.8101	< 0.005
	Intercept	–	e₀	− 0.91	0.18257	− 5.0065	< 0.005

^aInput variables with coefficient b_k are the values of shift (Δ) in q-reacvs. r-reac for different properties: α average atomic polarizability, EA average atomic Electro Affinity, χ average atomic Sanderson Electronegativity, Zv average atomic number
^bCoefficients of the variables in the model, the output variable is the Δ in enantiomeric excess ee(%)^* of the q-reac with respect to the r-reac when both reactions have been carried out with(R)-catalyst
^cStandard error of the coefficients
^dStudent t-value
^ep-level of error

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